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Record W2221273530 · doi:10.1109/pvsc.2015.7356063

Identifying representative air masses for multi-junction solar cell bandgap optimization to maximize annual energy yield

2015· article· en· W2221273530 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
Topicsolar cell performance optimization
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsYield (engineering)Band gapAir mass (solar energy)Energy (signal processing)Solar energyAir gap (plumbing)Energy consumptionSkyPoint (geometry)Solar cellEnvironmental scienceOptoelectronicsMaterials scienceMeteorologyPhysicsElectrical engineeringMathematicsEngineeringStatistics

Abstract

fetched live from OpenAlex

Annual energy yield is calculated for multijunction solar cells with ideal bandgap combinations optimized for spectra between AM0.7d and AM3.1d. A “representative spectrum” can thus be defined, within the assumptions of the study, as that which corresponds to the air mass that resulted in the highest annual energy yield. Results show that the air mass of this representative spectrum does not correspond to the 50% cumulative energy air mass which has traditionally been used as a point of reference. Further, the optimal design point is shown to be different for cells with different numbers of junctions. Bandgap combinations that maximize clear sky annual energy yield in Boulder, USA and Ottawa, Canada are presented.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.170
Threshold uncertainty score0.864

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.057
GPT teacher head0.270
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations2
Published2015
Admission routes2
Has abstractyes

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